When interpreting the contents of images the detection of regions is a very important step in the analysis. Typically these regions are characterized in that one or more features within these regions are either relatively constant or vary in a predetermined manner. In other words, the features within these regions are considered to be consistent within the region. Such features may for example be local dominant orientation, local spatial frequency, the degree of curvature or a description of texture features and texture parameters. However, in such detection of regions, one of the problems heretofore encountered has been the difficulty in distinguishing between low level noise in the image and characterizing features that are not stable. Attempts to overcome this problem have centered around efforts in areas relating to computerized image analysis and in particular to methods which have been implemented by means of a program for use with a general purpose computer. However, such methods have been inherently slow.